kernelshap: Kernel SHAP

Efficient implementation of Kernel SHAP, see Lundberg and Lee (2017), and Covert and Lee (2021) <http://proceedings.mlr.press/v130/covert21a>. Furthermore, for up to 14 features, exact permutation SHAP values can be calculated. The package plays well together with meta-learning packages like 'tidymodels', 'caret' or 'mlr3'. Visualizations can be done using the R package 'shapviz'.

Version:	0.4.1
Depends:	R (≥ 3.2.0)
Imports:	foreach, stats, utils
Suggests:	doFuture, testthat (≥ 3.0.0)
Published:	2023-12-03
Author:	Michael Mayer [aut, cre], David Watson [aut], Przemyslaw Biecek [ctb]
Maintainer:	Michael Mayer <mayermichael79 at gmail.com>
BugReports:	https://github.com/ModelOriented/kernelshap/issues
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:	https://github.com/ModelOriented/kernelshap
NeedsCompilation:	no
Materials:	README NEWS
In views:	MachineLearning
CRAN checks:	kernelshap results

Documentation:

Reference manual:

kernelshap.pdf

Downloads:

Package source:	kernelshap_0.4.1.tar.gz
Windows binaries:	r-devel: kernelshap_0.4.1.zip, r-release: kernelshap_0.4.1.zip, r-oldrel: kernelshap_0.4.1.zip
macOS binaries:	r-release (arm64): kernelshap_0.4.1.tgz, r-oldrel (arm64): kernelshap_0.4.1.tgz, r-release (x86_64): kernelshap_0.4.1.tgz, r-oldrel (x86_64): kernelshap_0.4.1.tgz
Old sources:	kernelshap archive

Reverse dependencies:

Reverse imports:

survex

Linking:

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